Create README.md

README.md

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+I'll explain more about this model when I've found the optimal checkpoint for its use case
+
+it's been full fine-tuned on [Sandevistan](https://huggingface.co/datasets/Replete-AI/Sandevistan).
+
+
+Here is my Axolotl config (thanks to fizz and empti):
+
+```
+base_model: meta-llama/Meta-Llama-3-8B
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: Kquant03/Sandevistan_Reformat
+    type: customllama3_stan
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.05
+output_dir: ./outputs/out
+max_steps: 80000
+
+fix_untrained_tokens: true
+
+sequence_len: 4096
+sample_packing: true
+pad_to_sequence_len: true
+
+wandb_project: Pneuma
+wandb_entity: 
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 16
+micro_batch_size: 8
+num_epochs: 1
+optimizer: paged_adamw_8bit
+lr_scheduler: cosine
+learning_rate: 0.00001
+max_grad_norm: 1
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: unsloth
+early_stopping_patience:
+resume_from_checkpoint:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+eval_sample_packing: false
+
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_swiglu: true
+liger_fused_linear_cross_entropy: true
+
+hub_model_id: Replete-AI/L3-Pneuma-8B
+hub_strategy: every_save
+
+warmup_steps: 10
+evals_per_epoch: 3
+eval_table_size:
+saves_per_epoch: 3
+debug:
+deepspeed:
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<|begin_of_text|>"
+  eos_token: "<|end_of_text|>"
+  pad_token: "<|end_of_text|>"
+tokens:
+```